Posts filed under ‘Statistics & Research Methods’

Effect size, in a nutshell, is a value which allows you to see how much your independent variable (IV) has affected the dependent variable (DV) in an experimental study. In other words, it looks at how much variance in your DV was a result of the IV. You can only calculate an effect size after conducting an appropriate statistical test for significance. This post will look at effect size with ANOVA (ANalysis Of VAriables), which is not the same as other tests (like a t-test). When using effect size with ANOVA, we use η² (Eta squared), rather than Cohen’s d with a t-test, for example.

Rate this:

SPSS (or PASW as it is now known), forms a huge part of most Psychology degrees for students. Admittedly, many students cringe at the thought of Statistics, or even maths in general. However, SPSS is a very important program to master, especially for those interested in pursuing a career in research, or for the brave, a career involving teaching Research Methods.

I’ve decided, beings a lot of people struggle to understand Research Methods or the statistical concepts behind SPSS, that I’d share my knowledge of the subject. I’m no Statistics master, but I’ve done Research Methods for 3 years now, and have an AS level in Stats as well. Hopefully this ‘crash course’ in SPSS will be of benefit to some students, and maybe help me consolidate my learning also. I’m sorry to any casual readers who do not take Psychology, and were hoping for something slightly more generalised. I’m sure there will be many people who will find this information of use though. Let me know what you think. If you have any specific requests for topics regarding SPSS, feel free to e-mail me (psychohawks@gmail.com)

I’ll also point out that these are susceptible to updates, as I learn more about the subjects. So if the information you need isn’t here at the moment, check back to make sure it isn’t added in the near future. Terms in bold are included in the glossary (see the pages menu on the right).

SPSS – part one.
Custom Tables – why are they useful?

Custom tables allow the user to quickly view important information about sets of data. Measures of central tendency can be viewed easily, and you can choose yourself what you want to be shown in the table. Another common statistic that is shown in custom tables is the standard deviation (σ). The best feature of the custom table is the ability to completely customise the layout. You can have the variables anywhere you want, and show whatever statistic you want for any variables you choose. Therefore, the custom table is very important for reporting results and is nearly always included in a lab report.

How do I make a custom table?

The method to get a custom table is slightly different for within groups and between groups. I’ll explain the within groups first.
Consider the following data (just to point out, the data is fabricated):

The next thing we’d want to do with this data is find the important statistics, such as the ones mentioned above. How do we get to a custom table though? You need to go to Analyse > Tables > Custom Tables, as seen below.

This will being up the custom tables screen. You should notice your variables on the left, in a window. The variables here are “BeforeTreatment” and “AfterTreatment”. The next step is to drag the first variable over to the “rows” bar. Drop it, and it’ll form a small table.

You’ll need to repeat the process with the remaining variable. However, you need to make sure the variable forms a line underneath the variable you just dragged over, as seen below.

Notice the burgundy(ish?) line underneath the “BeforeTreatment” cell? This tells SPSS to place the variable underneath. However, you’ll notice only the mean is displayed. This is fine if that’s all you want, simply press okay and the table will be displayed, with the statistics, in a pop-up “Output” window. However, most of the time you’ll want to see more than just the mean. So how do we go about that? Simply click the “Summary Statistics” button at the bottom left. This is shown by a red ring on the screenshot below.

This will bring up another window, as shown above. I’ll use colours for the steps, to correspond to the rings on the diagram above. Next, select a variable you want. Mode and median are examples of some you may wish to use, but there are many available. You can use the scroll bar to explore the options. Once you’ve selected one, press the arrow button to move the option over to the selections on the right. If you change your mind, select the variable on the right and press the arrow button again to move it back. Once you’ve selected all the variables you want, press the “Apply to All” button (shown in yellow – the yellow font was hard to read!). This makes sure all cells in your custom table will display the statistics you’ve selected – for all variables. Then press the OK button on the original screen. The table will then be created in the output window:

There you have it! A fully customised table displaying exactly the statistics you want to see. From this table, you can compare means and standard deviation to get a “feel” for the data. From this, it would seem the data is significant – although a statistical test would have to confirm this!

If you feel I haven’t covered the topic sufficiently, please let me know how I could improve this post.
Thanks very much. If you like the blog – please subscribe and you’ll be kept up-to-date!